list_subscriptionsList the caller's active subscriptions. Returns id, type, params, created_at, last_fired_at, fire_count for each. Use this to review what you're monitoring before adding more or to find an id to cancel.
| Name | Required | Description | Default |
|---|---|---|---|
| include_inactive | No | Include cancelled subscriptions in the response (default false). |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, destructiveHint. Description adds return field list and default active-only filter, which is useful but not essential beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences that front-load the main action and add value in the second sentence. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one optional parameter, the description covers purpose, usage, return fields, and parameter context. No output schema needed as fields are described.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with description for the sole parameter. Description adds no new information beyond what schema provides, so baseline score applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'List the caller's active subscriptions' with a specific verb and resource. Distinguishes from siblings like 'subscribe' and 'unsubscribe' by focusing on enumeration.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit use cases: 'review what you're monitoring before adding more or to find an id to cancel.' Lacks explicit when-not-to-use but context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Multiple tools appear to do the same thing: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all provide natural-language data lookup, with ask_pipeworx_beta explicitly identical to ask_pipeworx. The six Polymarket tools also have heavily overlapping boundaries, and the Census-specific tools overlap with each other and with ask_pipeworx's routing to Census data.
All names are lowercase snake_case, which is consistent, but the pattern is a mix: some are verb_noun (discover_tools, generate_llms_txt, list_subscriptions) while many are noun_verb or bare noun phrases (entity_profile, pipeworx_feedback, polymarket_edges, census_acs). Suffixes like _beta, _grounded, and the scattered noun-first names prevent a uniform convention.
36 tools is well into the too-heavy range for a coherent server. Even if the domain truly is broad data research and prediction markets, many of these tools are near-duplicates or serve the same purpose with minor variations, so the count feels inflated rather than scoped.
The broad data-research domain is well covered: single lookups (ask_pipeworx), grounded verification (ask_pipeworx_grounded, validate_claim), multi-source research (deep_research, entitity_profile, compare_entities, recent_changes), plus memory and subscription utilities. Minor gaps exist (e.g., no general data update/delete, but data is read-only; no direct Census variable explorer beyond census_available_datasets), but no critical dead ends appear.